Latest from MIT Tech Review – A chatbot helped more people access mental-health services

An AI chatbot helped increase the number of patients referred for mental-health services through England’s National Health Service (NHS), particularly among underrepresented groups who are less likely to seek help, new research has found. Demand for mental-health services in England is on the rise, particularly since the covid-19 pandemic. Mental-health services received 4.6 million patient…

Latest from MIT : How symmetry can come to the aid of machine learning

Behrooz Tahmasebi — an MIT PhD student in the Department of Electrical Engineering and Computer Science (EECS) and an affiliate of the Computer Science and Artificial Intelligence Laboratory (CSAIL) — was taking a mathematics course on differential equations in late 2021 when a glimmer of inspiration struck. In that class, he learned for the first…

Latest from MIT : Doctors have more difficulty diagnosing disease when looking at images of darker skin

When diagnosing skin diseases based solely on images of a patient’s skin, doctors do not perform as well when the patient has darker skin, according to a new study from MIT researchers. The study, which included more than 1,000 dermatologists and general practitioners, found that dermatologists accurately characterized about 38 percent of the images they…

Latest from Google AI – A decoder-only foundation model for time-series forecasting

Posted by Rajat Sen and Yichen Zhou, Google Research Time-series forecasting is ubiquitous in various domains, such as retail, finance, manufacturing, healthcare and natural sciences. In retail use cases, for example, it has been observed that improving demand forecasting accuracy can meaningfully reduce inventory costs and increase revenue. Deep learning (DL) models have emerged as…

Latest from Google AI – Intervening on early readouts for mitigating spurious features and simplicity bias

Posted by Rishabh Tiwari, Pre-doctoral Researcher, and Pradeep Shenoy, Research Scientist, Google Research Machine learning models in the real world are often trained on limited data that may contain unintended statistical biases. For example, in the CELEBA celebrity image dataset, a disproportionate number of female celebrities have blond hair, leading to classifiers incorrectly predicting “blond”…

Latest from MIT Tech Review – This robot can tidy a room without any help

Robots are good at certain tasks. They’re great at picking up and moving objects, for example, and they’re even getting better at cooking. But while robots may easily complete tasks like these in a laboratory, getting them to work in an unfamiliar environment where there’s little data available is a real challenge. Now, a new…

Latest from Google AI – MobileDiffusion: Rapid text-to-image generation on-device

Posted by Yang Zhao, Senior Software Engineer, and Tingbo Hou, Senior Staff Software Engineer, Core ML Text-to-image diffusion models have shown exceptional capabilities in generating high-quality images from text prompts. However, leading models feature billions of parameters and are consequently expensive to run, requiring powerful desktops or servers (e.g., Stable Diffusion, DALL·E, and Imagen). While…

Latest from MIT Tech Review – Dear Taylor Swift, we’re sorry about those explicit deepfakes

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Hi, Taylor. I can only imagine how you must be feeling after sexually explicit deepfake videos of you went viral on X. Disgusted. Distressed, perhaps. Humiliated, even.  I’m really sorry this is…

Latest from MIT Tech Review – Three ways we can fight deepfake porn

Last week, sexually explicit images of Taylor Swift, one of the world’s biggest pop stars, went viral online. Millions of people viewed nonconsensual deepfake porn of Swift on the social media platform X, formerly known as Twitter. X has since taken the drastic step of blocking all searches for Taylor Swift to try to get…

Latest from Google AI – Mixed-input matrix multiplication performance optimizations

Posted by Manish Gupta, Staff Software Engineer, Google Research AI-driven technologies are weaving themselves into the fabric of our daily routines, with the potential to enhance our access to knowledge and boost our overall productivity. The backbone of these applications lies in large language models (LLMs). LLMs are memory-intensive and typically require specialized hardware accelerators…